Data summary
Name dat
Number of rows 500
Number of columns 5
_______________________
Column type frequency:
numeric 5
________________________
Group variables None

Variable type: numeric

skim_variable n_missing complete_rate mean sd p0 p25 p50 p75 p100 hist
V1 0 1 8.13 9.82 -17.28 0.52 7.01 14.79 45.67 ▁▇▆▂▁
V2 0 1 -0.18 11.38 -43.28 -7.67 0.96 6.81 39.61 ▁▂▇▃▁
V3 0 1 0.33 9.75 -33.39 -6.38 0.65 7.29 30.54 ▁▃▇▅▁
V4 0 1 0.44 10.05 -28.53 -7.79 0.59 9.00 28.57 ▁▆▇▆▁
V5 0 1 0.39 10.36 -30.85 -8.61 0.68 8.89 29.29 ▁▆▇▇▁

Simulation from sim_pDim_kCl()

View simulation

Cluster #1, level: cl b

column means:

##       V1       V2       V3       V4       V5 
##  0.43457  1.31718 -0.04885  9.96364  9.92084

column ggcorr:

Cluster #2, level: cl c

column means:

##      V1      V2      V3      V4      V5 
## 10.0844 -0.2670  0.1087  0.5503  0.5052

column ggcorr:

Cluster differneces; cluster 2 - cluster 1

column means:

##      V1      V2      V3      V4      V5 
##  9.6498 -1.5842  0.1575 -9.4134 -9.4156

column ggcorr:

LDA

## Call:
## lda(dat, grouping = clas)
## 
## Prior probabilities of groups:
## cl b cl c cl a 
##  0.1  0.8  0.1 
## 
## Group means:
##           V1     V2       V3      V4       V5
## cl b  0.4346  1.317 -0.04885  9.9636   9.9208
## cl c 10.0844 -0.267  0.10867  0.5503   0.5052
## cl a  0.1503 -1.007  2.47480 -9.9307 -10.0203
## 
## Coefficients of linear discriminants:
##          LD1       LD2
## V1 -0.007472 -0.110349
## V2 -0.006776  0.002333
## V3  0.008456  0.016209
## V4 -0.080285  0.008986
## V5 -0.075444  0.003564
## 
## Proportion of trace:
##    LD1    LD2 
## 0.7208 0.2792

PCA Scree

## Standard deviations (1, .., p=5):
## [1] 11.415 11.036 10.021  9.543  9.265
## 
## Rotation (n x k) = (5 x 5):
##         PC1      PC2       PC3      PC4     PC5
## V1 -0.04224  0.04756 -0.789633 -0.50294  0.3457
## V2  0.98593 -0.12357  0.007765 -0.03285  0.1074
## V3  0.02224 -0.17544 -0.570261  0.79283 -0.1223
## V4  0.15389  0.60934 -0.209137 -0.13362 -0.7372
## V5  0.04459  0.76184  0.086507  0.31551  0.5573

clSep; orig, orig vs MMP, MMp

Original variable cluster seperation:

Original vs MMP cluster seperation:

MMP cluster seperation:

As factors in the user study

Answer

PCA

Manual tour (radial)

Grand tour

Apendix

ClSep of Single-variable permutations (sim_pDim_kCl)